https://github.com/qecsim/tensornetworkcodes.jl

TensorNetworkCodes is a Julia library developed to support the following research: https://arxiv.org/abs/2109.11996
https://github.com/qecsim/tensornetworkcodes.jl

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TensorNetworkCodes is a Julia library developed to support the following research: https://arxiv.org/abs/2109.11996

• Host: GitHub
• URL: https://github.com/qecsim/tensornetworkcodes.jl
• Owner: qecsim
• License: bsd-3-clause
• Created: 2021-07-27T03:03:52.000Z (almost 5 years ago)
• Default Branch: main
• Last Pushed: 2023-11-25T11:42:00.000Z (over 2 years ago)
• Last Synced: 2025-01-20T22:51:07.402Z (over 1 year ago)
• Language: Jupyter Notebook
• Homepage:
• Size: 3.7 MB
• Stars: 8
• Watchers: 4
• Forks: 2
• Open Issues: 3
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# TensorNetworkCodes

[![Stable](https://img.shields.io/badge/docs-stable-blue.svg)](https://qecsim.github.io/TensorNetworkCodes.jl/stable)

[![Dev](https://img.shields.io/badge/docs-dev-blue.svg)](https://qecsim.github.io/TensorNetworkCodes.jl/dev)

[![Build Status](https://github.com/qecsim/TensorNetworkCodes.jl/workflows/CI/badge.svg)](https://github.com/qecsim/TensorNetworkCodes.jl/actions)

[![Coverage](https://codecov.io/gh/qecsim/TensorNetworkCodes.jl/branch/main/graph/badge.svg?token=M4ATXN9DIK)](https://codecov.io/gh/qecsim/TensorNetworkCodes.jl)

## Introduction

[TensorNetworkCodes.jl](https://github.com/qecsim/TensorNetworkCodes.jl) is a Julia library

developed to support the following research:

* T. Farrelly, D. K. Tuckett, T. M. Stace, _Local tensor-network codes_,

  [arXiv:2109.11996](https://arxiv.org/abs/2109.11996), (2021).

## Installation

_TensorNetworkCodes.jl_ is installed, like any other registered Julia package,

using the Julia package manager [Pkg](https://pkgdocs.julialang.org/):

```julia

pkg> add TensorNetworkCodes  # Press ']' to enter the Pkg REPL mode.

```

or

```julia

julia> using Pkg; Pkg.add("TensorNetworkCodes")

```

## Demos

The following demos correspond to results included in

[arXiv:2109.11996](https://arxiv.org/abs/2109.11996):

* [Small example tensor-network codes and code distances](https://nbviewer.org/github/qecsim/TensorNetworkCodes.jl/blob/main/nbs/Small_examples_with_distance.ipynb)

* [The 19 qubit colour code as a tensor-network code](https://nbviewer.org/github/qecsim/TensorNetworkCodes.jl/blob/main/nbs/Colour_code.ipynb)

* [The modified surface code](https://nbviewer.org/github/qecsim/TensorNetworkCodes.jl/blob/main/nbs/Modified_surface_code_example.ipynb)

## Citing

Please cite _TensorNetworkCodes.jl_ if you use it in your research.

A suitable BibTeX entry is:

    @article{Farrelly_LocalTNCodes_2021,

        title = {Local tensor-network codes},

        author = {Farrelly, Terry and Tuckett, David K. and Stace, Thomas M.},

        year = {2021},

        archiveprefix = {arXiv},

        eprint = {2109.11996},

        url = {https://arxiv.org/abs/2109.11996},

    }

Similarly, please cite [Qecsim.jl](https://github.com/qecsim/Qecsim.jl) if you use its

features in your research, see

[Qecsim.jl Documentation](https://qecsim.github.io/Qecsim.jl/) for details.

## License

_TensorNetworkCodes.jl_ is released under the BSD 3-Clause license, see

[LICENSE](https://github.com/qecsim/TensorNetworkCodes.jl/blob/main/LICENSE).

## Links

* Source code: 

* Documentation: 

* Contact: Terry Farrelly [farreltc@tcd.ie](mailto:farreltc@tcd.ie)